knitr::opts_chunk$set(echo = FALSE,cache = TRUE)
library(xlsx)
library(ggplot2)
## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlang
library(gplots)
##
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
##
## lowess
library(gridExtra)
library(corrplot)
## corrplot 0.84 loaded
library(dplyr)
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:gridExtra':
##
## combine
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(png)
library(grid)
library(heatmaply)
## Loading required package: plotly
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
## Loading required package: viridis
## Loading required package: viridisLite
## Registered S3 method overwritten by 'seriation':
## method from
## reorder.hclust gclus
##
## ======================
## Welcome to heatmaply version 0.16.0
##
## Type citation('heatmaply') for how to cite the package.
## Type ?heatmaply for the main documentation.
##
## The github page is: https://github.com/talgalili/heatmaply/
## Please submit your suggestions and bug-reports at: https://github.com/talgalili/heatmaply/issues
## Or contact: <tal.galili@gmail.com>
## ======================
## Warning: NAs introduced by coercion
## Tree.ID Allocation Column Row Rep. measure Height Flower Flower.Level
## 840 IN4E4 F1 2 20 N 7 M N 0
## 1363 IN4FM F1 3 17 N 11 H N 0
## Chl Flav Anth Height08 Height09 HD
## 840 18.511 1.401 0.370 138 234 96
## 1363 59.122 1.640 0.483 166 245 79
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 8 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 8 rows containing non-finite values (stat_bin).
## Warning: Removed 8 rows containing non-finite values (stat_density).
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 9 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 9 rows containing non-finite values (stat_bin).
## Warning: Removed 9 rows containing non-finite values (stat_density).
## Warning: Removed 1811 rows containing non-finite values (stat_boxplot).
## Warning: Removed 180 rows containing missing values (geom_point).
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 180 rows containing non-finite values (stat_bin).
## Warning: Removed 180 rows containing non-finite values (stat_density).
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 0.0000 1.650e-06 0.001 0.999
## Residuals 1787 3.0326 1.697e-03
##
## Call:
## lm(formula = F1$Anth5 ~ F1$Height)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.108092 -0.027610 -0.000777 0.025741 0.198752
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.737e-05 1.846e-03 -0.036 0.971
## F1$HeightL 8.195e-05 2.452e-03 0.033 0.973
## F1$HeightM 1.049e-04 2.461e-03 0.043 0.966
##
## Residual standard error: 0.04119 on 1787 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 1.089e-06, Adjusted R-squared: -0.001118
## F-statistic: 0.000973 on 2 and 1787 DF, p-value: 0.999
## 2.5 % 97.5 %
## (Intercept) -0.003687902 0.003553152
## F1$HeightL -0.004728010 0.004891906
## F1$HeightM -0.004721273 0.004931111
## [1] 1.08897e-06
## Warning in cor.test.default(HM$Anth, HH$Anth, method = "spearman"): Cannot
## compute exact p-value with ties
##
## Spearman's rank correlation rho
##
## data: HM$Anth and HH$Anth
## S = 701463, p-value = 0.5556
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.04708476
## Warning in cor.test.default(HH$Anth, HL$Anth, method = "spearman"): Cannot
## compute exact p-value with ties
##
## Spearman's rank correlation rho
##
## data: HH$Anth and HL$Anth
## S = 725230, p-value = 0.3008
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.08256216
##
## Spearman's rank correlation rho
##
## data: HM$Anth and HL$Anth
## S = 691294, p-value = 0.6894
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.0319053
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 802 401.03 1.8488 0.1577
## Residuals 1787 387632 216.92
## 2.5 % 97.5 %
## (Intercept) -2.34392260 0.2449164
## F1$HeightL -0.08648552 3.3528501
## F1$HeightM -0.45338321 2.9975606
## [1] 0.002064874
##
## Spearman's rank correlation rho
##
## data: HM$Chl and HH$Chl
## S = 780026, p-value = 0.03853
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.1643569
##
## Spearman's rank correlation rho
##
## data: HH$Chl and HL$Chl
## S = 793142, p-value = 0.02041
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.1839354
##
## Spearman's rank correlation rho
##
## data: HM$Chl and HL$Chl
## S = 731494, p-value = 0.2489
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.09191247
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height 2 0.001 0.000562 0.0102 0.9899
## Residuals 1787 98.658 0.055209
## 2.5 % 97.5 %
## (Intercept) -0.02186947 0.01943162
## F1$HeightL -0.02547173 0.02939778
## F1$HeightM -0.02611714 0.02893756
## [1] 1.139096e-05
##
## Spearman's rank correlation rho
##
## data: HM$Flav and HH$Flav
## S = 578494, p-value = 0.08629
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.136473
##
## Spearman's rank correlation rho
##
## data: HH$Flav and HL$Flav
## S = 619624, p-value = 0.3466
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.07507762
##
## Spearman's rank correlation rho
##
## data: HM$Flav and HL$Flav
## S = 520262, p-value = 0.004727
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.2233968
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0.00009 0.00000191 0.0011 1
## Residuals 1740 3.03249 0.00174281
##
## Call:
## lm(formula = F1$Anth5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10823 -0.02772 -0.00075 0.02580 0.19883
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.236e-04 6.026e-03 -0.021 0.984
## F1$Row10 -4.004e-04 9.527e-03 -0.042 0.966
## F1$Row11 1.971e-06 8.478e-03 0.000 1.000
## F1$Row12 2.002e-04 9.527e-03 0.021 0.983
## F1$Row13 6.312e-05 9.819e-03 0.006 0.995
## F1$Row14 1.970e-04 9.440e-03 0.021 0.983
## F1$Row15 1.970e-04 9.440e-03 0.021 0.983
## F1$Row16 1.123e-05 9.716e-03 0.001 0.999
## F1$Row17 5.573e-04 1.092e-02 0.051 0.959
## F1$Row18 1.123e-05 9.716e-03 0.001 0.999
## F1$Row19 1.970e-04 9.440e-03 0.021 0.983
## F1$Row2 1.970e-04 9.440e-03 0.021 0.983
## F1$Row20 6.273e-05 8.766e-03 0.007 0.994
## F1$Row21 1.432e-04 9.133e-03 0.016 0.987
## F1$Row22 1.970e-04 9.440e-03 0.021 0.983
## F1$Row23 6.273e-05 8.766e-03 0.007 0.994
## F1$Row24 6.013e-04 9.440e-03 0.064 0.949
## F1$Row25 1.970e-04 9.440e-03 0.021 0.983
## F1$Row26 6.852e-04 9.619e-03 0.071 0.943
## F1$Row27 4.335e-04 9.527e-03 0.045 0.964
## F1$Row28 1.970e-04 9.440e-03 0.021 0.983
## F1$Row29 -4.004e-04 9.527e-03 -0.042 0.966
## F1$Row3 1.970e-04 9.440e-03 0.021 0.983
## F1$Row30 -1.846e-04 9.716e-03 -0.019 0.985
## F1$Row31 -4.212e-04 8.766e-03 -0.048 0.962
## F1$Row32 1.970e-04 8.713e-03 0.023 0.982
## F1$Row33 1.970e-04 9.440e-03 0.021 0.983
## F1$Row34 1.970e-04 8.713e-03 0.023 0.982
## F1$Row35 2.890e-05 8.662e-03 0.003 0.997
## F1$Row36 2.002e-04 9.527e-03 0.021 0.983
## F1$Row37 2.002e-04 9.527e-03 0.021 0.983
## F1$Row38 -1.756e-04 9.619e-03 -0.018 0.985
## F1$Row39 1.970e-04 9.440e-03 0.021 0.983
## F1$Row4 -2.072e-04 9.440e-03 -0.022 0.982
## F1$Row40 1.970e-04 9.440e-03 0.021 0.983
## F1$Row41 3.156e-04 8.567e-03 0.037 0.971
## F1$Row42 3.751e-04 9.440e-03 0.040 0.968
## F1$Row43 2.548e-04 9.619e-03 0.026 0.979
## F1$Row44 4.335e-04 9.527e-03 0.045 0.964
## F1$Row45 6.273e-05 8.766e-03 0.007 0.994
## F1$Row46 5.096e-04 8.766e-03 0.058 0.954
## F1$Row47 -1.109e-04 8.766e-03 -0.013 0.990
## F1$Row48 1.899e-05 9.440e-03 0.002 0.998
## F1$Row49 1.970e-04 8.713e-03 0.023 0.982
## F1$Row5 2.002e-04 9.527e-03 0.021 0.983
## F1$Row50 -1.715e-04 8.178e-03 -0.021 0.983
## F1$Row6 1.970e-04 9.440e-03 0.021 0.983
## F1$Row7 1.970e-04 9.440e-03 0.021 0.983
## F1$Row8 1.970e-04 9.440e-03 0.021 0.983
## F1$Row9 -2.550e-05 9.358e-03 -0.003 0.998
##
## Residual standard error: 0.04175 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 3.078e-05, Adjusted R-squared: -0.02813
## F-statistic: 0.001093 on 49 and 1740 DF, p-value: 1
## [1] -9.57882e-18
## 2.5 % 97.5 %
## (Intercept) -0.01194186 0.01169474
## F1$Row10 -0.01908672 0.01828602
## F1$Row11 -0.01662614 0.01663008
## F1$Row12 -0.01848620 0.01888655
## F1$Row13 -0.01919444 0.01932068
## F1$Row14 -0.01831868 0.01871275
## F1$Row15 -0.01831868 0.01871275
## F1$Row16 -0.01904520 0.01906766
## F1$Row17 -0.02086516 0.02197981
## F1$Row18 -0.01904520 0.01906766
## F1$Row19 -0.01831868 0.01871275
## F1$Row2 -0.01831868 0.01871275
## F1$Row20 -0.01712986 0.01725533
## F1$Row21 -0.01776961 0.01805600
## F1$Row22 -0.01831868 0.01871275
## F1$Row23 -0.01712986 0.01725533
## F1$Row24 -0.01791440 0.01911703
## F1$Row25 -0.01831868 0.01871275
## F1$Row26 -0.01818116 0.01955152
## F1$Row27 -0.01825289 0.01911985
## F1$Row28 -0.01831868 0.01871275
## F1$Row29 -0.01908672 0.01828602
## F1$Row3 -0.01831868 0.01871275
## F1$Row30 -0.01924106 0.01887181
## F1$Row31 -0.01761375 0.01677144
## F1$Row32 -0.01689220 0.01728627
## F1$Row33 -0.01831868 0.01871275
## F1$Row34 -0.01689220 0.01728627
## F1$Row35 -0.01696098 0.01701877
## F1$Row36 -0.01848620 0.01888655
## F1$Row37 -0.01848620 0.01888655
## F1$Row38 -0.01904189 0.01869079
## F1$Row39 -0.01831868 0.01871275
## F1$Row4 -0.01872296 0.01830847
## F1$Row40 -0.01831868 0.01871275
## F1$Row41 -0.01648663 0.01711790
## F1$Row42 -0.01814063 0.01889080
## F1$Row43 -0.01861153 0.01912115
## F1$Row44 -0.01825289 0.01911985
## F1$Row45 -0.01712986 0.01725533
## F1$Row46 -0.01668296 0.01770223
## F1$Row47 -0.01730348 0.01708171
## F1$Row48 -0.01849673 0.01853470
## F1$Row49 -0.01689220 0.01728627
## F1$Row5 -0.01848620 0.01888655
## F1$Row50 -0.01621181 0.01586877
## F1$Row6 -0.01831868 0.01871275
## F1$Row7 -0.01831868 0.01871275
## F1$Row8 -0.01831868 0.01871275
## F1$Row9 -0.01837915 0.01832815
## [1] 3.078204e-05
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0 0.00 0 1
## Residuals 1740 388434 223.24
##
## Call:
## lm(formula = F1$Chl5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -40.413 -10.889 1.258 11.488 30.448
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.122e-14 2.157e+00 0 1
## F1$Row10 -5.443e-14 3.410e+00 0 1
## F1$Row11 -5.868e-14 3.034e+00 0 1
## F1$Row12 -4.608e-14 3.410e+00 0 1
## F1$Row13 -4.346e-14 3.514e+00 0 1
## F1$Row14 -4.472e-14 3.379e+00 0 1
## F1$Row15 -5.143e-14 3.379e+00 0 1
## F1$Row16 -4.709e-14 3.477e+00 0 1
## F1$Row17 -2.396e-14 3.909e+00 0 1
## F1$Row18 -4.307e-14 3.477e+00 0 1
## F1$Row19 -8.068e-14 3.379e+00 0 1
## F1$Row2 -3.876e-14 3.379e+00 0 1
## F1$Row20 -5.483e-14 3.137e+00 0 1
## F1$Row21 -5.324e-14 3.269e+00 0 1
## F1$Row22 -5.665e-14 3.379e+00 0 1
## F1$Row23 -5.097e-14 3.137e+00 0 1
## F1$Row24 -3.762e-14 3.379e+00 0 1
## F1$Row25 -4.563e-14 3.379e+00 0 1
## F1$Row26 -5.032e-14 3.443e+00 0 1
## F1$Row27 -5.458e-14 3.410e+00 0 1
## F1$Row28 -4.724e-14 3.379e+00 0 1
## F1$Row29 -3.408e-14 3.410e+00 0 1
## F1$Row3 -4.192e-14 3.379e+00 0 1
## F1$Row30 -5.594e-14 3.477e+00 0 1
## F1$Row31 1.341e-14 3.137e+00 0 1
## F1$Row32 -5.711e-14 3.118e+00 0 1
## F1$Row33 -5.905e-14 3.379e+00 0 1
## F1$Row34 -5.094e-14 3.118e+00 0 1
## F1$Row35 -6.647e-14 3.100e+00 0 1
## F1$Row36 -5.311e-14 3.410e+00 0 1
## F1$Row37 -9.871e-15 3.410e+00 0 1
## F1$Row38 -4.983e-14 3.443e+00 0 1
## F1$Row39 -5.183e-14 3.379e+00 0 1
## F1$Row4 -5.165e-14 3.379e+00 0 1
## F1$Row40 -6.223e-14 3.379e+00 0 1
## F1$Row41 -5.581e-14 3.066e+00 0 1
## F1$Row42 -5.669e-14 3.379e+00 0 1
## F1$Row43 -5.319e-14 3.443e+00 0 1
## F1$Row44 -7.369e-14 3.410e+00 0 1
## F1$Row45 -6.561e-14 3.137e+00 0 1
## F1$Row46 -8.051e-14 3.137e+00 0 1
## F1$Row47 -6.965e-14 3.137e+00 0 1
## F1$Row48 -6.373e-14 3.379e+00 0 1
## F1$Row49 -4.888e-14 3.118e+00 0 1
## F1$Row5 -6.082e-14 3.410e+00 0 1
## F1$Row50 -6.229e-14 2.927e+00 0 1
## F1$Row6 -4.716e-14 3.379e+00 0 1
## F1$Row7 -6.638e-14 3.379e+00 0 1
## F1$Row8 -6.942e-14 3.379e+00 0 1
## F1$Row9 -7.645e-14 3.349e+00 0 1
##
## Residual standard error: 14.94 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 1.668e-29, Adjusted R-squared: -0.02816
## F-statistic: 5.924e-28 on 49 and 1740 DF, p-value: 1
## [1] 1.668271e-29
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 0.200 0.004090 0.0723 1
## Residuals 1740 98.459 0.056585
##
## Call:
## lm(formula = F1$Flav5 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87631 -0.14319 0.01576 0.15006 0.83162
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0160350 0.0343346 -0.467 0.641
## F1$Row10 0.0122635 0.0542877 0.226 0.821
## F1$Row11 -0.0007709 0.0483081 -0.016 0.987
## F1$Row12 0.0109164 0.0542877 0.201 0.841
## F1$Row13 0.0113525 0.0559472 0.203 0.839
## F1$Row14 0.0109282 0.0537920 0.203 0.839
## F1$Row15 0.0109282 0.0537920 0.203 0.839
## F1$Row16 0.0159958 0.0553629 0.289 0.773
## F1$Row17 0.0285742 0.0622367 0.459 0.646
## F1$Row18 0.0110881 0.0553629 0.200 0.841
## F1$Row19 0.0109282 0.0537920 0.203 0.839
## F1$Row2 0.0109282 0.0537920 0.203 0.839
## F1$Row20 0.0175783 0.0499480 0.352 0.725
## F1$Row21 0.0067765 0.0520404 0.130 0.896
## F1$Row22 0.0109282 0.0537920 0.203 0.839
## F1$Row23 0.0370839 0.0499480 0.742 0.458
## F1$Row24 0.0073530 0.0537920 0.137 0.891
## F1$Row25 0.0109282 0.0537920 0.203 0.839
## F1$Row26 0.0089356 0.0548106 0.163 0.871
## F1$Row27 0.0094440 0.0542877 0.174 0.862
## F1$Row28 0.0109282 0.0537920 0.203 0.839
## F1$Row29 0.0147885 0.0542877 0.272 0.785
## F1$Row3 0.0109282 0.0537920 0.203 0.839
## F1$Row30 0.0118640 0.0553629 0.214 0.830
## F1$Row31 0.0048055 0.0499480 0.096 0.923
## F1$Row32 0.0352480 0.0496477 0.710 0.478
## F1$Row33 0.0109282 0.0537920 0.203 0.839
## F1$Row34 0.0352480 0.0496477 0.710 0.478
## F1$Row35 0.0346724 0.0493591 0.702 0.482
## F1$Row36 0.0124501 0.0542877 0.229 0.819
## F1$Row37 0.0124501 0.0542877 0.229 0.819
## F1$Row38 0.0128693 0.0548106 0.235 0.814
## F1$Row39 0.0109282 0.0537920 0.203 0.839
## F1$Row4 0.0125355 0.0537920 0.233 0.816
## F1$Row40 0.0109282 0.0537920 0.203 0.839
## F1$Row41 0.0218259 0.0488140 0.447 0.655
## F1$Row42 0.0107487 0.0537920 0.200 0.842
## F1$Row43 0.0095752 0.0548106 0.175 0.861
## F1$Row44 0.0109777 0.0542877 0.202 0.840
## F1$Row45 0.0359426 0.0499480 0.720 0.472
## F1$Row46 0.0357126 0.0499480 0.715 0.475
## F1$Row47 0.0350335 0.0499480 0.701 0.483
## F1$Row48 0.0106271 0.0537920 0.198 0.843
## F1$Row49 0.0352480 0.0496477 0.710 0.478
## F1$Row5 0.0124501 0.0542877 0.229 0.819
## F1$Row50 0.0200420 0.0466003 0.430 0.667
## F1$Row6 0.0109282 0.0537920 0.203 0.839
## F1$Row7 0.0109282 0.0537920 0.203 0.839
## F1$Row8 0.0109282 0.0537920 0.203 0.839
## F1$Row9 0.0123251 0.0533211 0.231 0.817
##
## Residual standard error: 0.2379 on 1740 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 0.002032, Adjusted R-squared: -0.02607
## F-statistic: 0.07229 on 49 and 1740 DF, p-value: 1
## [1] 0.002031552
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 24288 495.68 2.1009 1.659e-05 ***
## Residuals 1672 394486 235.94
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Call:
## lm(formula = F1$H185 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -52.933 -11.518 -0.736 11.531 39.018
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.5699 2.5252 3.394 0.000706 ***
## F1$Row10 -7.3312 3.7081 -1.977 0.048195 *
## F1$Row11 -4.5365 3.3454 -1.356 0.175273
## F1$Row12 -6.7638 3.7081 -1.824 0.068317 .
## F1$Row13 -6.0953 3.8095 -1.600 0.109780
## F1$Row14 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row15 -0.6156 4.1353 -0.149 0.881685
## F1$Row16 -7.9814 3.7738 -2.115 0.034581 *
## F1$Row17 -10.2487 4.1353 -2.478 0.013299 *
## F1$Row18 -5.8621 3.7738 -1.553 0.120521
## F1$Row19 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row2 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row20 -6.0017 3.4444 -1.742 0.081610 .
## F1$Row21 -7.0921 3.5476 -1.999 0.045758 *
## F1$Row22 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row23 -14.8322 3.4444 -4.306 1.76e-05 ***
## F1$Row24 -7.9433 3.6491 -2.177 0.029636 *
## F1$Row25 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row26 -8.4962 3.7081 -2.291 0.022071 *
## F1$Row27 -11.9432 4.1353 -2.888 0.003926 **
## F1$Row28 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row29 -10.9642 4.1966 -2.613 0.009066 **
## F1$Row3 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row30 -8.7014 3.7400 -2.327 0.020106 *
## F1$Row31 -6.0018 3.4262 -1.752 0.080001 .
## F1$Row32 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row33 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row34 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row35 -14.1328 3.4088 -4.146 3.55e-05 ***
## F1$Row36 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row37 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row38 -7.9288 3.7081 -2.138 0.032640 *
## F1$Row39 -2.1704 4.0786 -0.532 0.594691
## F1$Row4 -0.6156 4.1353 -0.149 0.881685
## F1$Row40 -2.1704 4.0786 -0.532 0.594691
## F1$Row41 -11.1135 3.3759 -3.292 0.001015 **
## F1$Row42 -8.0326 3.6491 -2.201 0.027854 *
## F1$Row43 -7.2665 3.7081 -1.960 0.050201 .
## F1$Row44 -8.3034 3.6778 -2.258 0.024093 *
## F1$Row45 -14.3393 3.4444 -4.163 3.30e-05 ***
## F1$Row46 -14.8322 3.4444 -4.306 1.76e-05 ***
## F1$Row47 -13.9652 3.4444 -4.055 5.25e-05 ***
## F1$Row48 -8.5666 3.6491 -2.348 0.019011 *
## F1$Row49 -14.4746 3.4262 -4.225 2.52e-05 ***
## F1$Row5 -0.6879 4.1966 -0.164 0.869820
## F1$Row50 -10.3134 3.2428 -3.180 0.001498 **
## F1$Row6 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row7 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row8 -7.1737 3.6778 -1.951 0.051279 .
## F1$Row9 -7.5595 3.6491 -2.072 0.038456 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.36 on 1672 degrees of freedom
## (89 observations deleted due to missingness)
## Multiple R-squared: 0.058, Adjusted R-squared: 0.03039
## F-statistic: 2.101 on 49 and 1672 DF, p-value: 1.659e-05
## [1] "numeric"
## Warning in cor.test.default(F1$Anth5, F1$Row2, method = "spearman"): Cannot
## compute exact p-value with ties
##
## Spearman's rank correlation rho
##
## data: F1$Anth5 and F1$Row2
## S = 954253100, p-value = 0.9423
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.00171195
## [1] 0.05799867
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 36836 751.76 3.2009 1.777e-12 ***
## Residuals 1671 392453 234.86
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Call:
## lm(formula = F1$H195 ~ F1$Row)
##
## Residuals:
## Min 1Q Median 3Q Max
## -47.068 -9.354 1.204 10.862 38.322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.495 2.519 4.959 7.79e-07 ***
## F1$Row10 -11.677 3.700 -3.156 0.001626 **
## F1$Row11 -7.027 3.338 -2.105 0.035411 *
## F1$Row12 -10.852 3.700 -2.933 0.003399 **
## F1$Row13 -9.877 3.801 -2.599 0.009444 **
## F1$Row14 -11.478 3.669 -3.128 0.001791 **
## F1$Row15 -1.467 4.126 -0.356 0.722127
## F1$Row16 -12.841 3.765 -3.410 0.000664 ***
## F1$Row17 -17.664 4.187 -4.219 2.59e-05 ***
## F1$Row18 -9.476 3.765 -2.517 0.011939 *
## F1$Row19 -11.478 3.669 -3.128 0.001791 **
## F1$Row2 -11.478 3.669 -3.128 0.001791 **
## F1$Row20 -9.992 3.436 -2.908 0.003691 **
## F1$Row21 -10.820 3.540 -3.057 0.002272 **
## F1$Row22 -12.346 3.641 -3.391 0.000713 ***
## F1$Row23 -19.346 3.436 -5.629 2.12e-08 ***
## F1$Row24 -12.133 3.641 -3.333 0.000879 ***
## F1$Row25 -12.346 3.641 -3.391 0.000713 ***
## F1$Row26 -13.026 3.700 -3.521 0.000442 ***
## F1$Row27 -18.724 4.126 -4.538 6.08e-06 ***
## F1$Row28 -12.346 3.641 -3.391 0.000713 ***
## F1$Row29 -15.926 4.187 -3.804 0.000148 ***
## F1$Row3 -11.478 3.669 -3.128 0.001791 **
## F1$Row30 -13.282 3.731 -3.559 0.000382 ***
## F1$Row31 -9.051 3.418 -2.648 0.008180 **
## F1$Row32 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row33 -12.346 3.641 -3.391 0.000713 ***
## F1$Row34 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row35 -18.390 3.401 -5.407 7.32e-08 ***
## F1$Row36 -12.785 3.669 -3.484 0.000506 ***
## F1$Row37 -12.785 3.669 -3.484 0.000506 ***
## F1$Row38 -12.200 3.700 -3.298 0.000995 ***
## F1$Row39 -3.186 4.069 -0.783 0.433764
## F1$Row4 -1.467 4.126 -0.356 0.722127
## F1$Row40 -3.186 4.069 -0.783 0.433764
## F1$Row41 -14.762 3.368 -4.383 1.24e-05 ***
## F1$Row42 -12.346 3.641 -3.391 0.000713 ***
## F1$Row43 -11.149 3.700 -3.014 0.002621 **
## F1$Row44 -12.785 3.669 -3.484 0.000506 ***
## F1$Row45 -18.563 3.436 -5.402 7.55e-08 ***
## F1$Row46 -19.346 3.436 -5.629 2.12e-08 ***
## F1$Row47 -18.342 3.436 -5.337 1.07e-07 ***
## F1$Row48 -13.123 3.641 -3.604 0.000322 ***
## F1$Row49 -18.857 3.418 -5.516 4.00e-08 ***
## F1$Row5 -1.640 4.187 -0.392 0.695367
## F1$Row50 -13.308 3.235 -4.113 4.09e-05 ***
## F1$Row6 -11.478 3.669 -3.128 0.001791 **
## F1$Row7 -11.478 3.669 -3.128 0.001791 **
## F1$Row8 -11.478 3.669 -3.128 0.001791 **
## F1$Row9 -12.067 3.641 -3.314 0.000938 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.33 on 1671 degrees of freedom
## (90 observations deleted due to missingness)
## Multiple R-squared: 0.08581, Adjusted R-squared: 0.059
## F-statistic: 3.201 on 49 and 1671 DF, p-value: 1.777e-12
## 2.5 % 97.5 %
## (Intercept) 7.553141 17.436343
## F1$Row10 -18.933812 -4.421146
## F1$Row11 -13.573779 -0.480487
## F1$Row12 -18.108467 -3.595800
## F1$Row13 -17.331566 -2.421807
## F1$Row14 -18.674913 -4.280640
## F1$Row15 -9.559984 6.625003
## F1$Row16 -20.225683 -5.455889
## F1$Row17 -25.876426 -9.451554
## F1$Row18 -16.860616 -2.090822
## F1$Row19 -18.674913 -4.280640
## F1$Row2 -18.674913 -4.280640
## F1$Row20 -16.731907 -3.251332
## F1$Row21 -17.762138 -3.877438
## F1$Row22 -19.486891 -5.204945
## F1$Row23 -26.085855 -12.605279
## F1$Row24 -19.273961 -4.992015
## F1$Row25 -19.486891 -5.204945
## F1$Row26 -20.282153 -5.769486
## F1$Row27 -26.816965 -10.631979
## F1$Row28 -19.486891 -5.204945
## F1$Row29 -24.138859 -7.713986
## F1$Row3 -18.674913 -4.280640
## F1$Row30 -20.600725 -5.963077
## F1$Row31 -15.755633 -2.346095
## F1$Row32 -25.561748 -12.152210
## F1$Row33 -19.486891 -5.204945
## F1$Row34 -25.561748 -12.152210
## F1$Row35 -25.060758 -11.719453
## F1$Row36 -19.982395 -5.588122
## F1$Row37 -19.982395 -5.588122
## F1$Row38 -19.456808 -4.944141
## F1$Row39 -11.167465 4.795346
## F1$Row4 -9.559984 6.625003
## F1$Row40 -11.167465 4.795346
## F1$Row41 -21.368203 -8.155601
## F1$Row42 -19.486891 -5.204945
## F1$Row43 -18.405224 -3.892558
## F1$Row44 -19.982395 -5.588122
## F1$Row45 -25.303281 -11.822706
## F1$Row46 -26.085855 -12.605279
## F1$Row47 -25.082439 -11.601863
## F1$Row48 -20.263686 -5.981741
## F1$Row49 -25.561748 -12.152210
## F1$Row5 -9.852299 6.572574
## F1$Row50 -19.654335 -6.962507
## F1$Row6 -18.674913 -4.280640
## F1$Row7 -18.674913 -4.280640
## F1$Row8 -18.674913 -4.280640
## F1$Row9 -19.207590 -4.925644
## [1] 0.08580726
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 50 rows containing missing values (geom_point).
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row 49 2380 48.577 0.2137 1
## Residuals 1671 379803 227.291
## 2.5 % 97.5 %
## (Intercept) -0.953871 8.768738
## F1$Row10 -11.472973 2.803876
## F1$Row11 -8.925979 3.954559
## F1$Row12 -11.215002 3.061848
## F1$Row13 -11.103379 3.564111
## F1$Row14 -11.372186 2.788193
## F1$Row15 -8.806285 7.115710
## F1$Row16 -12.110071 2.419728
## F1$Row17 -14.940314 1.217669
## F1$Row18 -10.867554 3.662245
## F1$Row19 -11.372186 2.788193
## F1$Row2 -11.372186 2.788193
## F1$Row20 -10.606094 2.655434
## F1$Row21 -10.547209 3.111877
## F1$Row22 -11.325831 2.724047
## F1$Row23 -11.128777 2.132751
## F1$Row24 -11.203181 2.846696
## F1$Row25 -11.325831 2.724047
## F1$Row26 -11.655292 2.621557
## F1$Row27 -14.719280 1.202715
## F1$Row28 -11.325831 2.724047
## F1$Row29 -13.033803 3.124181
## F1$Row3 -11.372186 2.788193
## F1$Row30 -11.767945 2.631854
## F1$Row31 -9.637477 3.554169
## F1$Row32 -10.963432 2.228214
## F1$Row33 -11.325831 2.724047
## F1$Row34 -10.963432 2.228214
## F1$Row35 -10.805262 2.319260
## F1$Row36 -11.548980 2.611399
## F1$Row37 -11.548980 2.611399
## F1$Row38 -11.397321 2.879529
## F1$Row39 -8.860010 6.843421
## F1$Row4 -8.806285 7.115710
## F1$Row40 -8.860010 6.843421
## F1$Row41 -10.136252 2.861659
## F1$Row42 -11.325831 2.724047
## F1$Row43 -11.009034 3.267815
## F1$Row44 -11.548980 2.611399
## F1$Row45 -10.839820 2.421709
## F1$Row46 -11.128777 2.132751
## F1$Row47 -10.993098 2.268430
## F1$Row48 -11.568627 2.481250
## F1$Row49 -10.963432 2.228214
## F1$Row5 -9.023567 7.134417
## F1$Row50 -9.229181 3.256416
## F1$Row6 -11.372186 2.788193
## F1$Row7 -11.372186 2.788193
## F1$Row8 -11.372186 2.788193
## F1$Row9 -11.519683 2.530195
+R.squared
## [1] 0.006228143
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 0.00847 0.0028245 1.6681 0.1719
## Residuals 1786 3.02411 0.0016932
## [1] 0.002794171
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 1961 653.53 3.0201 0.02876 *
## Residuals 1786 386473 216.39
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.005047411
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 0.011 0.003626 0.0657 0.9781
## Residuals 1786 98.648 0.055234
## [1] 0.0001102635
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 15817 5272.4 22.479 2.826e-14 ***
## Residuals 1718 402957 234.6
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.03776989
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 23664 7887.8 33.389 < 2.2e-16 ***
## Residuals 1717 405626 236.2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.05512251
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column 3 1938 646.10 2.9175 0.03306 *
## Residuals 1717 380245 221.46
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.005071636
Flowering refers to presence or not of flowers, Flower Level refers to a measure relating to the number of flowers present (0 = no flowers, 1 = 1-10, 2 = 10-20, 3 = 20+)
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 0.00336 0.0011185 0.6595 0.577
## Residuals 1786 3.02923 0.0016961
## [1] 0.001106519
##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR1$Anth
## t = 0.10961, df = 17.641, p-value = 0.914
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.007844330 0.008706595
## sample estimates:
## mean of x mean of y
## -4.216424e-05 -4.732968e-04
##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR2$Anth
## t = 0.48384, df = 9.6247, p-value = 0.6393
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.006494169 0.010072631
## sample estimates:
## mean of x mean of y
## -4.216424e-05 -1.831395e-03
##
## Welch Two Sample t-test
##
## data: FLWR0$Anth and FLWR3$Anth
## t = -1.1413, df = 10.155, p-value = 0.28
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.015283754 0.004915834
## sample estimates:
## mean of x mean of y
## -4.216424e-05 5.141795e-03
##
## Welch Two Sample t-test
##
## data: FLWR1$Anth and FLWR2$Anth
## t = 0.26272, df = 21.657, p-value = 0.7953
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.009372419 0.012088616
## sample estimates:
## mean of x mean of y
## -0.0004732968 -0.0018313954
##
## Welch Two Sample t-test
##
## data: FLWR1$Anth and FLWR3$Anth
## t = -0.96756, df = 20.452, p-value = 0.3446
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.017703586 0.006473401
## sample estimates:
## mean of x mean of y
## -0.0004732968 0.0051417955
##
## Welch Two Sample t-test
##
## data: FLWR2$Anth and FLWR3$Anth
## t = -1.2349, df = 16.578, p-value = 0.2341
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.018909645 0.004963264
## sample estimates:
## mean of x mean of y
## -0.001831395 0.005141795
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 0.00014 0.00014274 0.0842 0.7718
## Residuals 1788 3.03244 0.00169600
## [1] 4.70678e-05
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 1113 370.91 1.7103 0.1629
## Residuals 1786 387321 216.87
## [1] 0.002864653
##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR1$Chl
## t = -0.86203, df = 18.114, p-value = 0.3999
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -3.262209 1.363413
## sample estimates:
## mean of x mean of y
## -0.09097607 0.85842200
##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR2$Chl
## t = -2.0943, df = 9.079, p-value = 0.06546
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -5.8214337 0.2205142
## sample estimates:
## mean of x mean of y
## -0.09097607 2.70948366
##
## Welch Two Sample t-test
##
## data: FLWR0$Chl and FLWR3$Chl
## t = 0.83396, df = 10.12, p-value = 0.4236
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.928795 4.242233
## sample estimates:
## mean of x mean of y
## -0.09097607 -1.24769509
##
## Welch Two Sample t-test
##
## data: FLWR1$Chl and FLWR2$Chl
## t = -1.1099, df = 17.858, p-value = 0.2818
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -5.356882 1.654759
## sample estimates:
## mean of x mean of y
## 0.858422 2.709484
##
## Welch Two Sample t-test
##
## data: FLWR1$Chl and FLWR3$Chl
## t = 1.2331, df = 19.048, p-value = 0.2325
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.468068 5.680302
## sample estimates:
## mean of x mean of y
## 0.858422 -1.247695
##
## Welch Two Sample t-test
##
## data: FLWR2$Chl and FLWR3$Chl
## t = 2.1175, df = 16.993, p-value = 0.04926
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.01431469 7.90004282
## sample estimates:
## mean of x mean of y
## 2.709484 -1.247695
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 39 39.177 0.1804 0.6711
## Residuals 1788 388395 217.223
## [1] 0.0001008579
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 0.590 0.19672 3.5826 0.01335 *
## Residuals 1786 98.069 0.05491
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.00598177
##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR1$Flav
## t = -0.1909, df = 20.328, p-value = 0.8505
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.04941507 0.04112080
## sample estimates:
## mean of x mean of y
## -0.0048934073 -0.0007462706
##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR2$Flav
## t = -2.2842, df = 8.9901, p-value = 0.04826
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1564348449 -0.0007465781
## sample estimates:
## mean of x mean of y
## -0.004893407 0.073697304
##
## Welch Two Sample t-test
##
## data: FLWR0$Flav and FLWR3$Flav
## t = -0.58994, df = 9.9979, p-value = 0.5683
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.10199136 0.05929043
## sample estimates:
## mean of x mean of y
## -0.004893407 0.016457057
##
## Welch Two Sample t-test
##
## data: FLWR1$Flav and FLWR2$Flav
## t = -1.9087, df = 13.878, p-value = 0.07721
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.158165728 0.009278579
## sample estimates:
## mean of x mean of y
## -0.0007462706 0.0736973042
##
## Welch Two Sample t-test
##
## data: FLWR1$Flav and FLWR3$Flav
## t = -0.42387, df = 14.871, p-value = 0.6777
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1037772 0.0693705
## sample estimates:
## mean of x mean of y
## -0.0007462706 0.0164570573
##
## Welch Two Sample t-test
##
## data: FLWR2$Flav and FLWR3$Flav
## t = 1.1785, df = 17, p-value = 0.2548
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.04523505 0.15971554
## sample estimates:
## mean of x mean of y
## 0.07369730 0.01645706
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 0.245 0.244694 4.4456 0.03513 *
## Residuals 1788 98.414 0.055042
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.002480194
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 11639 3879.6 16.371 1.718e-10 ***
## Residuals 1718 407135 237.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.02779275
##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR1$H18
## t = -1.6305, df = 17.703, p-value = 0.1207
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -18.48037 2.34066
## sample estimates:
## mean of x mean of y
## -2.410131 5.659726
##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR2$H18
## t = -0.81929, df = 6.4906, p-value = 0.4417
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -22.95103 11.27931
## sample estimates:
## mean of x mean of y
## -2.410131 3.425728
##
## Welch Two Sample t-test
##
## data: FLWR0$H18 and FLWR3$H18
## t = -1.5807, df = 9.3853, p-value = 0.147
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -19.310608 3.365938
## sample estimates:
## mean of x mean of y
## -2.410131 5.562204
##
## Welch Two Sample t-test
##
## data: FLWR1$H18 and FLWR2$H18
## t = 0.26453, df = 11.816, p-value = 0.7959
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.19812 20.66612
## sample estimates:
## mean of x mean of y
## 5.659726 3.425728
##
## Welch Two Sample t-test
##
## data: FLWR1$H18 and FLWR3$H18
## t = 0.014376, df = 20.604, p-value = 0.9887
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -14.02649 14.22153
## sample estimates:
## mean of x mean of y
## 5.659726 5.562204
##
## Welch Two Sample t-test
##
## data: FLWR2$H18 and FLWR3$H18
## t = -0.25133, df = 11.217, p-value = 0.8061
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -20.80233 16.52937
## sample estimates:
## mean of x mean of y
## 3.425728 5.562204
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 2126 2125.89 8.776 0.003094 **
## Residuals 1720 416648 242.24
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.005076449
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 8766 2922.09 11.931 9.858e-08 ***
## Residuals 1717 420523 244.92
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.02042042
##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR1$H19
## t = -1.7634, df = 18.363, p-value = 0.09447
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -17.725963 1.535942
## sample estimates:
## mean of x mean of y
## -1.992529 6.102482
##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR2$H19
## t = -0.12465, df = 6.2813, p-value = 0.9047
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -24.14341 21.77867
## sample estimates:
## mean of x mean of y
## -1.9925285 -0.8101606
##
## Welch Two Sample t-test
##
## data: FLWR0$H19 and FLWR3$H19
## t = 0.3993, df = 9.2524, p-value = 0.6987
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -9.983022 14.284387
## sample estimates:
## mean of x mean of y
## -1.992529 -4.143211
##
## Welch Two Sample t-test
##
## data: FLWR1$H19 and FLWR2$H19
## t = 0.66835, df = 8.7152, p-value = 0.5212
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.60158 30.42687
## sample estimates:
## mean of x mean of y
## 6.1024818 -0.8101606
##
## Welch Two Sample t-test
##
## data: FLWR1$H19 and FLWR3$H19
## t = 1.5106, df = 18.391, p-value = 0.1479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -3.982633 24.474019
## sample estimates:
## mean of x mean of y
## 6.102482 -4.143211
##
## Welch Two Sample t-test
##
## data: FLWR2$H19 and FLWR3$H19
## t = 0.31093, df = 9.5696, p-value = 0.7625
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -20.69819 27.36429
## sample estimates:
## mean of x mean of y
## -0.8101606 -4.1432112
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 343 342.61 1.373 0.2415
## Residuals 1719 428947 249.53
## [1] 0.0007980757
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level 3 11642 3880.7 17.982 1.719e-11 ***
## Residuals 1717 370541 215.8
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.03046189
##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR1$HD5
## t = 0.0726, df = 22.1, p-value = 0.9428
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -6.781665 7.273837
## sample estimates:
## mean of x mean of y
## 0.6780263 0.4319402
##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR2$HD5
## t = 1.4803, df = 9.0022, p-value = 0.1729
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -2.604488 12.467963
## sample estimates:
## mean of x mean of y
## 0.6780263 -4.2537116
##
## Welch Two Sample t-test
##
## data: FLWR0$HD5 and FLWR3$HD5
## t = 2.0307, df = 9.4119, p-value = 0.07149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.10757 21.88518
## sample estimates:
## mean of x mean of y
## 0.6780263 -9.7107801
##
## Welch Two Sample t-test
##
## data: FLWR1$HD5 and FLWR2$HD5
## t = 1.0896, df = 17.451, p-value = 0.2907
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -4.369425 13.740729
## sample estimates:
## mean of x mean of y
## 0.4319402 -4.2537116
##
## Welch Two Sample t-test
##
## data: FLWR1$HD5 and FLWR3$HD5
## t = 1.7507, df = 14.317, p-value = 0.1014
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -2.257682 22.543123
## sample estimates:
## mean of x mean of y
## 0.4319402 -9.7107801
##
## Welch Two Sample t-test
##
## data: FLWR2$HD5 and FLWR3$HD5
## t = 0.94742, df = 12.738, p-value = 0.3611
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -7.012502 17.926639
## sample estimates:
## mean of x mean of y
## -4.253712 -9.710780
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).
## Analysis of Variance Table
##
## Response: F1$HD5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower 1 4205 4205.2 19.125 1.298e-05 ***
## Residuals 1719 377978 219.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.01100306
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
### Anthocyanin and Chlorophyll
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Chl5 1 0.31585 0.315847 207.87 < 2.2e-16 ***
## Residuals 1788 2.71674 0.001519
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.104151
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flav5 1 0.09389 0.093889 57.125 6.493e-14 ***
## Residuals 1788 2.93870 0.001644
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.03096008
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 0.00124 0.0012373 0.7231 0.3953
## Residuals 1699 2.90726 0.0017112
## [1] 0.0004254108
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 0.00004 0.00004488 0.0262 0.8714
## Residuals 1699 2.90846 0.00171186
## [1] 1.54299e-05
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 0.00193 0.0019302 1.1283 0.2883
## Residuals 1699 2.90657 0.0017108
## [1] 0.0006636417
## Analysis of Variance Table
##
## Response: F1$Anth5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flav5 1 0.09389 0.093889 57.125 6.493e-14 ***
## Residuals 1788 2.93870 0.001644
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.03096008
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 443 443.05 2.0322 0.1542
## Residuals 1699 370412 218.02
## [1] 0.001194672
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 57 56.603 0.2594 0.6106
## Residuals 1699 370798 218.245
## [1] 0.0001526278
## Analysis of Variance Table
##
## Response: F1$Chl5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 197 196.57 0.901 0.3426
## Residuals 1699 370658 218.16
## [1] 0.0005300545
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185 1 0.076 0.076208 1.3799 0.2403
## Residuals 1699 93.832 0.055228
## [1] 0.0008115148
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 0.201 0.201298 3.6497 0.05625 .
## Residuals 1699 93.707 0.055154
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.002143548
## Analysis of Variance Table
##
## Response: F1$Flav5
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 0.584 0.58427 10.637 0.001131 **
## Residuals 1699 93.324 0.05493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.006221659
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195 1 125710 125710 740.77 < 2.2e-16 ***
## Residuals 1719 291720 170
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.3011528
## Analysis of Variance Table
##
## Response: F1$H185
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 89593 89593 469.78 < 2.2e-16 ***
## Residuals 1719 327837 191
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.2146297
## Analysis of Variance Table
##
## Response: F1$H195
## Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5 1 101633 101633 533.2 < 2.2e-16 ***
## Residuals 1719 327656 191
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.2146297